This book takes a learner-oriented approach as it strives to make complex material understandable and usable. By understanding the underlying principles of measurement and evaluation, readers will then be able to apply those principles and concepts in a variety of physical activity and health-related settings. Practical exercises and applications demonstrate the usefulness of measurement and evaluation, reinforce key points, and make readers active participants in their own education. The book is divided into three parts. Part One introduces the measurement process, showing readers the relevance of measurement and evaluation to their personal and professional lives, and including examples and statistics related to such concepts as validity, reliability, and objectivity. The two chapters in Part Two further help readers understand numbers and assist those who need to use more advanced statistical calculations. Part Three presents measurement and evaluation applications in various settings, such as measuring physical fitness; measuring exercise, physical activity, and health; measuring in competitive sports and coaching; measuring and evaluating knowledge and assigning grades; and measuring in research. Throughout, discussions and examples show the relevance and application of measurement and evaluation in various professions, including physical therapy, athletic training, fitness/wellness management, exercise and sport psychology, exercise science, coaching, and physical education.

A premium college football player is estimated to generate over $1 million for his program, so optimal player assessment and selection are paramount. Lean body mass, back squat, and vertical jump have been the most predictive physical test scores, but such metrics typically account for less than 10% of variance in football performance. NFL scouts have tended to rely on vertical jump, 40-yard dash, and 20-yard shuttle scores, but interestingly, reliance on none of the physical tests conducted at the NFL Combine was predictive of team success; in fact, teams that relied on fewer total physical test scores tended to win more games. Dr. Tom Osborne suggested the Performance Index for interpreting physical performance metrics, but also insisted that psychological attributes such as toughness were equally important to his evaluation process since players deal with immense adversity during the course of a season. Toughness can be characterized as the ability to cope with stressors more effectively, and is measured in this study by examining cortisol reactivity. When physical test scores (i.e., lean body mass, hang clean, back squat, bench press, 10-yard dash, 20-yard shuttle, and vertical jump) were converted into Performance Index scores among 47 Division 1 freshman football players, players who contributed on the field differed from players who did not contribute only in vertical jump and 10-yard dash scores. A multiple regression model that included only physical test scores accounted for 28% of variance in football performance, whereas a model that included cortisol reactivity measured during a physical testing session, in addition to traditional physical performance prediction metrics, accounted for 39% of variance. Results from this investigation suggest that cortisol reactivity may capture a distinctive attribute of players and predict on-field performance better than many individual physical performance variables. If cortisol reactivity, as a measure of toughness, can be effectively used to predict performance on the football field, then the metric should be included in performance prediction models that have traditionally included only physical attributes of players.

Author's abstract: The recruiting process in collegiate football calls for coaches to identify prospective student-athletes who would be most successful at their institution. Humara (2005) argues that while coaches are experts in the identification of physical attributes needed for success, they may lack the ability to identify psychological skills. Niednagel (2004) would contend that in addition to psychological and physical factors, environmental factors also contribute to the ability to succeed. Participants were 108 male football players (35 linemen, 47 tight ends/linebackers, 18 skilled players, 8 special teams) from 6 teams in a NCAA Division I Southeastern conference. Using multivariate analysis of variance and discriminant analysis, the current research attempted to determine factors from demographic information, the Ten-Item Personality Inventory, and the Athletic Coping Skills Inventory-28, that most accurately predicts starting status in collegiate football players. Results showed that there was a significant difference between starters and non-starters for age, high school size, and coping with adversity, predicting starting status 79.6% of the time.

Measurement and Evaluation in Human Performance, Sixth Edition With HKPropel Access, teaches the fundamentals of collecting and analyzing human performance data by focusing on the concepts of reliability and validity. It features practical applications in kinesiology, physical education, and more